Integrating mixed methods analyses

The approach taken to integration of diverse data sources and analytical approaches in mixed methods studies is a crucial feature of those studies. Models of integration in analysis range from discussing separately generated results from different components or phases of a study together as part of the conclusion, through one method sequentially informing, expanding or confirming another, complementary combinations of data from different components and linking matched data sets to combination of data sources or conversion of data types to build a blended set of results. While different models of integration are appropriate for different research settings and purposes, an overcautious approach to integration can generate invalid or weakened conclusions through a failure to consider all available information together. Strategies for making the most of opportunities to integrate process and variable data in analysis, and to deal with dissonant or divergent results, in order to build strong and useful conclusions are explained and illustrated through reference to a variety of mixed methods studies from multiple disciplines.

Since graduating in psychology Dr Pat Bazeley has worked in community development, project consulting and in academic research development, both privately and as an academic. This has provided experience with research design and methodology across the social sciences, business and the professions. Her particular expertise is in helping researchers to make sense of qualitative and quantitative data and with integrating data from diverse sources and of different types, and in using computer programs for management and analysis of data. Pat was 2015-16 President of the Mixed Methods International Research Association, and is on the Editorial Boards of the Journal of Mixed Methods Research and Qualitative health Research. Her research and publications include books, chapters and articles focusing on qualitative and mixed methods data analysis, and on the development and performance of researchers.